Morning Brief

Google Ads Morning Brief

Produce a daily, prioritized account-health narrative for Google Ads campaigns with actionable items and budget pacing vs monthly target projection.

Account Context

Read ${CLAUDE_PLUGIN_ROOT}/profile/account-profile.md at the start of every run. If it exists:

• Use known account IDs -- skip list_accounts discovery.
• Apply KPI targets as anomaly detection thresholds (e.g., flag CPA > target CPA).
• Note active tests when interpreting performance shifts.
• Check watch list for follow-up items from prior sessions. If it doesn't exist, fall back to list_accounts and suggest running platform-setup.

Data Access

Google Ads

• mcp__google-ads__query: Execute GAQL SELECT queries and return structured rows.
• mcp__google-ads__list_accounts: Validate account access before reporting when customer scope is unclear.

Use GAQL templates from references/gaql-queries.md directly with mcp__google-ads__query.

Connection verification

1. If the profile has account IDs, use them directly.
2. Otherwise, run mcp__google-ads__list_accounts to discover accounts.
3. If it fails, report the connection failure and suggest running platform-setup.

Workflow

Phase 1: Collect data

Execute five queries from references/gaql-queries.md:

1. Campaign daily performance (30d).
2. Budget pacing and impression share (yesterday snapshot).
3. Disapproved ads.
4. High-spend, zero-conversion keywords (yesterday).
5. Recent account changes (last 24h).

Run queries 1-4 first. Query 5 can run in parallel since it has no dependency on the others.

Phase 2: Detect and rank anomalies

Use references/anomaly-formulas.md for exact formulas.

For each campaign, for each metric (cost, conversions, CPA, CTR):

1. Compute baseline_7d = mean of last 7 days (excluding yesterday).
2. Compute baseline_30d = mean of last 30 days (excluding yesterday).
3. Compute deviation_pct = (yesterday - baseline_7d) / baseline_7d.
4. Compute dollar_impact = yesterday_value - baseline_7d (for cost/CPA metrics). CTR is not dollar-denominated; use deviation_pct only.
5. Surface when BOTH: |deviation_pct| > 0.20 AND |dollar_impact| > $10. For CTR: surface when |deviation_pct| > 0.25 (no dollar gate).
6. Rank all flagged items by |dollar_impact| descending.

Cap output at 10 anomaly items to keep the brief actionable.

Phase 3: Budget pacing assessment

Google Ads daily budgets are daily targets, not monthly caps.

For each campaign:

1. daily_budget = campaign daily budget converted to dollars.
2. monthly_budget = daily_budget * 30.4.
3. day_of_month = calendar day number.
4. expected_mtd_spend = daily_budget * day_of_month.
5. actual_mtd_spend = sum of daily cost for current month from Query 1.
6. pacing_ratio = actual_mtd_spend / expected_mtd_spend.
7. Flag overpacing when pacing_ratio > 1.10 and underpacing when pacing_ratio < 0.85.

Monthly target projection

If the account profile includes a Monthly Budget target:

1. total_mtd_spend = sum of all campaign MTD spend.
2. projected_eom_spend = total_mtd_spend / day_of_month * days_in_month.
3. budget_utilization = projected_eom_spend / monthly_budget_target.
4. Flag when projected spend exceeds target by >10% or falls below target by >15%.

Present both campaign-level pacing and account-level monthly projection.

Phase 4: Draft prioritized narrative

Structure output with three priority tiers:

• Urgent: needs action today.
• Watch: monitor or schedule action.
• Healthy: stable areas.

Every item must include the likely cause and one concrete next action.

Output format

## Morning Brief - [Date]

### Account
- Google Ads: [Account Name] ([Customer ID]) - [N] campaigns active

**Overall:** [one-sentence account summary]

### Budget Pacing
| Campaign | Daily Budget | MTD Spend | Expected MTD | Pacing | Status |
|---|---:|---:|---:|---:|---|

**Monthly Projection:** $X,XXX projected vs $X,XXX target ([over/under] by X%)

### Urgent
1. [Issue + impact + recommended action]

### Watch
1. [Issue + impact + recommended action]

### Healthy
- [stability observation]

### Notes
- Data freshness and known caveats

Guardrails

• Conversion lag: When yesterday conversions are >30% below 7d baseline, add a note that conversions typically backfill for 24-72 hours. Do not flag as "Urgent" unless the drop also appears in 2-day-old data.
• Mention change-event delay (~3 min lag for Google) and timestamp cut-off.
• Distinguish between "no issues found" and "insufficient data".
• Keep recommendations operational and specific.
• Cap each priority section: max 5 Urgent, 5 Watch, 5 Healthy items.
• Read-only: This skill produces analysis and recommendations only. No account modifications are made. Recommended actions include Google Ads UI paths where applicable.

Profile Maintenance

After completing analysis, if ${CLAUDE_PLUGIN_ROOT}/profile/account-profile.md exists:

1. Update Watch List with any new anomalies flagged in this run.
2. Update Active Tests if user mentioned starting or completing a test.
3. Append to Decision Log if actions were taken (pauses, negatives added, etc.).
4. Update "Last updated" date. Present proposed profile changes to the user before writing.

References

• references/gaql-queries.md
• references/anomaly-formulas.md
• references/google-reporting.md